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fix readme #3071

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Oct 17, 2023
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fix readme #3071

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850b6fb
fix readme
WeberJulian Oct 16, 2023
3037bd0
fix inference.md
WeberJulian Oct 16, 2023
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15 changes: 8 additions & 7 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -198,17 +198,18 @@ from TTS.api import TTS
# Get device
device = "cuda" if torch.cuda.is_available() else "cpu"

# List available 🐸TTS models and choose the first one
model_name = TTS().list_models()[0]
# List available 🐸TTS models
print(TTS().list_models())

# Init TTS
tts = TTS(model_name).to(device)
tts = TTS("tts_models/multilingual/multi-dataset/xtts_v1").to(device)

# Run TTS
# ❗ Since this model is multi-speaker and multi-lingual, we must set the target speaker and the language
# Text to speech with a numpy output
wav = tts.tts("This is a test! This is also a test!!", speaker=tts.speakers[0], language=tts.languages[0])
# ❗ Since this model is multi-lingual voice cloning model, we must set the target speaker_wav and language
# Text to speech list of amplitude values as output
wav = tts.tts(text="Hello world!", speaker_wav="my/cloning/audio.wav", language="en")
# Text to speech to a file
tts.tts_to_file(text="Hello world!", speaker=tts.speakers[0], language=tts.languages[0], file_path="output.wav")
tts.tts_to_file(text="Hello world!", speaker_wav="my/cloning/audio.wav", language="en", file_path="output.wav")
```

#### Running a single speaker model
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20 changes: 13 additions & 7 deletions docs/source/inference.md
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Expand Up @@ -114,18 +114,24 @@ tts-server --model_name "<type>/<language>/<dataset>/<model_name>" \
You can run a multi-speaker and multi-lingual model in Python as

```python
import torch
from TTS.api import TTS

# List available 🐸TTS models and choose the first one
model_name = TTS().list_models()[0]
# Get device
device = "cuda" if torch.cuda.is_available() else "cpu"

# List available 🐸TTS models
print(TTS().list_models())

# Init TTS
tts = TTS(model_name)
tts = TTS("tts_models/multilingual/multi-dataset/xtts_v1").to(device)

# Run TTS
# ❗ Since this model is multi-speaker and multi-lingual, we must set the target speaker and the language
# Text to speech with a numpy output
wav = tts.tts("This is a test! This is also a test!!", speaker=tts.speakers[0], language=tts.languages[0])
# ❗ Since this model is multi-lingual voice cloning model, we must set the target speaker_wav and language
# Text to speech list of amplitude values as output
wav = tts.tts(text="Hello world!", speaker_wav="my/cloning/audio.wav", language="en")
# Text to speech to a file
tts.tts_to_file(text="Hello world!", speaker=tts.speakers[0], language=tts.languages[0], file_path="output.wav")
tts.tts_to_file(text="Hello world!", speaker_wav="my/cloning/audio.wav", language="en", file_path="output.wav")
```

#### Here is an example for a single speaker model.
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